Pixel-class prediction for nitrogen content of tea plants based on unmanned aerial vehicle images using machine learning and deep learning.
Shu-Mao WangJun-Hui MaZhu-Meng ZhaoHong-Zhi-Yuan YangYimin XuanJia-Xue OuyangDong-Mei FanJin-Feng YuXiao-Chang WangPublished in: Expert Syst. Appl. (2023)
Keyphrases
- deep learning
- machine learning
- input image
- unsupervised learning
- image analysis
- image features
- unmanned aerial vehicles
- ground truth
- pattern recognition
- image classification
- object recognition
- segmentation method
- image regions
- computer vision
- test images
- image retrieval
- target object
- bounding box
- feature selection
- deep belief networks